Pandas Profiling Report

Dataset statistics

Number of variables	21
Number of observations	740
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	26
Duplicate rows (%)	3.5%
Total size in memory	121.5 KiB
Average record size in memory	168.2 B

Variable types

Numeric	14
Categorical	7

Warnings

Dataset has 26 (3.5%) duplicate rows	Duplicates
`Reason for absence` is highly correlated with `Disciplinary failure`	High correlation
`Service time` is highly correlated with `Age`	High correlation
`Age` is highly correlated with `Service time`	High correlation
`Disciplinary failure` is highly correlated with `Reason for absence`	High correlation
`Weight` is highly correlated with `Body mass index`	High correlation
`Body mass index` is highly correlated with `Weight`	High correlation
`Service time` is highly correlated with `Age` and 2 other fields	High correlation
`Age` is highly correlated with `Service time`	High correlation
`Weight` is highly correlated with `Service time` and 1 other fields	High correlation
`Body mass index` is highly correlated with `Service time` and 1 other fields	High correlation
`Service time` is highly correlated with `Age`	High correlation
`Age` is highly correlated with `Service time`	High correlation
`Weight` is highly correlated with `Body mass index`	High correlation
`Body mass index` is highly correlated with `Weight`	High correlation
`Age` is highly correlated with `Height` and 9 other fields	High correlation
`Height` is highly correlated with `Age` and 10 other fields	High correlation
`ID` is highly correlated with `Age` and 10 other fields	High correlation
`Son` is highly correlated with `Age` and 8 other fields	High correlation
`Seasons` is highly correlated with `Month of absence` and 2 other fields	High correlation
`Reason for absence` is highly correlated with `Disciplinary failure`	High correlation
`Pet` is highly correlated with `Age` and 10 other fields	High correlation
`Transportation expense` is highly correlated with `Age` and 10 other fields	High correlation
`Body mass index` is highly correlated with `Age` and 11 other fields	High correlation
`Month of absence` is highly correlated with `Seasons` and 2 other fields	High correlation
`Work load Average/day` is highly correlated with `Seasons` and 2 other fields	High correlation
`Disciplinary failure` is highly correlated with `Reason for absence`	High correlation
`Weight` is highly correlated with `Age` and 11 other fields	High correlation
`Hit target` is highly correlated with `Seasons` and 2 other fields	High correlation
`Social smoker` is highly correlated with `Height` and 5 other fields	High correlation
`Distance from Residence to Work` is highly correlated with `Age` and 11 other fields	High correlation
`Education` is highly correlated with `Height` and 8 other fields	High correlation
`Service time` is highly correlated with `Age` and 10 other fields	High correlation
`Social drinker` is highly correlated with `Age` and 8 other fields	High correlation
`Reason for absence` has 43 (5.8%) zeros	Zeros
`Pet` has 460 (62.2%) zeros	Zeros
`Absenteeism time in hours` has 44 (5.9%) zeros	Zeros

Reproduction

Analysis started	2021-09-09 15:40:34.666047
Analysis finished	2021-09-09 15:41:00.469453
Duration	25.8 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

ID
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	36
Distinct (%)	4.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.01756757

Minimum	1
Maximum	36
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	9
median	18
Q3	28
95-th percentile	34
Maximum	36
Range	35
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	11.02124726
Coefficient of variation (CV)	0.6116945155
Kurtosis	-1.251818317
Mean	18.01756757
Median Absolute Deviation (MAD)	10
Skewness	0.01660590675
Sum	13333
Variance	121.4678912
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=36)

Value	Count	Frequency (%)
3	113	15.3%
28	76	10.3%
34	55	7.4%
22	46	6.2%
20	42	5.7%
11	40	5.4%
15	37	5.0%
36	34	4.6%
24	30	4.1%
14	29	3.9%
Other values (26)	238	32.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	23	3.1%
2	6	0.8%
3	113	15.3%
4	1	0.1%
5	19	2.6%
6	8	1.1%
7	6	0.8%
8	2	0.3%
9	8	1.1%
10	24	3.2%

Value	Count	Frequency (%)
36	34	4.6%
35	1	0.1%
34	55	7.4%
33	24	3.2%
32	5	0.7%
31	3	0.4%
30	7	0.9%
29	5	0.7%
28	76	10.3%
27	7	0.9%

Reason for absence
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	28
Distinct (%)	3.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	19.21621622

Minimum	0
Maximum	28
Zeros	43
Zeros (%)	5.8%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	13
median	23
Q3	26
95-th percentile	28
Maximum	28
Range	28
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	8.433405883
Coefficient of variation (CV)	0.4388692232
Kurtosis	-0.2599250726
Mean	19.21621622
Median Absolute Deviation (MAD)	5
Skewness	-0.9153123659
Sum	14220
Variance	71.12233478
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
23	149	20.1%
28	112	15.1%
27	69	9.3%
13	55	7.4%
0	43	5.8%
19	40	5.4%
22	38	5.1%
26	33	4.5%
25	31	4.2%
11	26	3.5%
Other values (18)	144	19.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	43	5.8%
1	16	2.2%
2	1	0.1%
3	1	0.1%
4	2	0.3%
5	3	0.4%
6	8	1.1%
7	15	2.0%
8	6	0.8%
9	4	0.5%

Value	Count	Frequency (%)
28	112	15.1%
27	69	9.3%
26	33	4.5%
25	31	4.2%
24	3	0.4%
23	149	20.1%
22	38	5.1%
21	6	0.8%
19	40	5.4%
18	21	2.8%

Month of absence
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.324324324

Minimum	0
Maximum	12
Zeros	3
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	6
Q3	9
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.436286932
Coefficient of variation (CV)	0.5433445149
Kurtosis	-1.254966504
Mean	6.324324324
Median Absolute Deviation (MAD)	3
Skewness	0.06936854151
Sum	4680
Variance	11.80806788
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
3	87	11.8%
2	72	9.7%
10	71	9.6%
7	67	9.1%
5	64	8.6%
11	63	8.5%
8	54	7.3%
6	54	7.3%
9	53	7.2%
4	53	7.2%
Other values (3)	102	13.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	0.4%
1	50	6.8%
2	72	9.7%
3	87	11.8%
4	53	7.2%
5	64	8.6%
6	54	7.3%
7	67	9.1%
8	54	7.3%
9	53	7.2%

Value	Count	Frequency (%)
12	49	6.6%
11	63	8.5%
10	71	9.6%
9	53	7.2%
8	54	7.3%
7	67	9.1%
6	54	7.3%
5	64	8.6%
4	53	7.2%
3	87	11.8%

Day of the week
Categorical

Distinct	5
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

2	161
4	156
3	154
6	144
5	125

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	3
3rd row	4
4th row	5
5th row	5

Common Values

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Most occurring characters

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	161	21.8%
4	156	21.1%
3	154	20.8%
6	144	19.5%
5	125	16.9%

Seasons
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

4	195
2	192
3	183
1	170

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Most occurring characters

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	195	26.4%
2	192	25.9%
3	183	24.7%
1	170	23.0%

Transportation expense
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	24
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	221.3297297

Minimum	118
Maximum	388
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	118
5-th percentile	118
Q1	179
median	225
Q3	260
95-th percentile	361
Maximum	388
Range	270
Interquartile range (IQR)	81

Descriptive statistics

Standard deviation	66.95222325
Coefficient of variation (CV)	0.3024999096
Kurtosis	-0.3182910179
Mean	221.3297297
Median Absolute Deviation (MAD)	46
Skewness	0.396188637
Sum	163784
Variance	4482.600197
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
179	180	24.3%
118	92	12.4%
225	81	10.9%
235	58	7.8%
289	45	6.1%
260	42	5.7%
291	40	5.4%
246	30	4.1%
155	29	3.9%
248	24	3.2%
Other values (14)	119	16.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
118	92	12.4%
155	29	3.9%
157	7	0.9%
179	180	24.3%
184	7	0.9%
189	8	1.1%
225	81	10.9%
228	8	1.1%
231	2	0.3%
233	7	0.9%

Value	Count	Frequency (%)
388	3	0.4%
378	8	1.1%
369	15	2.0%
361	24	3.2%
330	16	2.2%
300	5	0.7%
291	40	5.4%
289	45	6.1%
279	6	0.8%
268	3	0.4%

Distance from Residence to Work
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	25
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	29.63108108

Minimum	5
Maximum	52
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	5
5-th percentile	10
Q1	16
median	26
Q3	50
95-th percentile	51
Maximum	52
Range	47
Interquartile range (IQR)	34

Descriptive statistics

Standard deviation	14.83678844
Coefficient of variation (CV)	0.5007170814
Kurtosis	-1.261682574
Mean	29.63108108
Median Absolute Deviation (MAD)	11
Skewness	0.3120827847
Sum	21927
Variance	220.1302911
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
26	128	17.3%
51	120	16.2%
10	55	7.4%
25	54	7.3%
50	45	6.1%
36	40	5.4%
31	37	5.0%
13	34	4.6%
12	29	3.9%
11	26	3.5%
Other values (15)	172	23.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	6	0.8%
10	55	7.4%
11	26	3.5%
12	29	3.9%
13	34	4.6%
14	9	1.2%
15	9	1.2%
16	26	3.5%
17	15	2.0%
20	19	2.6%

Value	Count	Frequency (%)
52	24	3.2%
51	120	16.2%
50	45	6.1%
49	8	1.1%
48	5	0.7%
45	1	0.1%
42	7	0.9%
36	40	5.4%
35	2	0.3%
31	37	5.0%

Service time
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	18
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.55405405

Minimum	1
Maximum	29
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	1
5-th percentile	4
Q1	9
median	13
Q3	16
95-th percentile	18
Maximum	29
Range	28
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	4.384873408
Coefficient of variation (CV)	0.3492794749
Kurtosis	0.6831107752
Mean	12.55405405
Median Absolute Deviation (MAD)	4
Skewness	-0.004719563328
Sum	9290
Variance	19.2271148
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
18	147	19.9%
9	126	17.0%
14	85	11.5%
13	73	9.9%
12	61	8.2%
10	55	7.4%
11	50	6.8%
16	38	5.1%
3	24	3.2%
17	20	2.7%
Other values (8)	61	8.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	7	0.9%
3	24	3.2%
4	16	2.2%
6	7	0.9%
7	7	0.9%
8	13	1.8%
9	126	17.0%
10	55	7.4%
11	50	6.8%
12	61	8.2%

Value	Count	Frequency (%)
29	5	0.7%
24	2	0.3%
18	147	19.9%
17	20	2.7%
16	38	5.1%
15	4	0.5%
14	85	11.5%
13	73	9.9%
12	61	8.2%
11	50	6.8%

Age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	22
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	36.45

Minimum	27
Maximum	58
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	27
5-th percentile	28
Q1	31
median	37
Q3	40
95-th percentile	50
Maximum	58
Range	31
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	6.478772458
Coefficient of variation (CV)	0.1777441003
Kurtosis	0.4316130531
Mean	36.45
Median Absolute Deviation (MAD)	4
Skewness	0.6977034092
Sum	26973
Variance	41.97449256
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
28	117	15.8%
38	113	15.3%
37	78	10.5%
40	58	7.8%
33	51	6.9%
36	50	6.8%
30	46	6.2%
50	37	5.0%
41	34	4.6%
34	29	3.9%
Other values (12)	127	17.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
27	7	0.9%
28	117	15.8%
29	7	0.9%
30	46	6.2%
31	22	3.0%
32	13	1.8%
33	51	6.9%
34	29	3.9%
36	50	6.8%
37	78	10.5%

Value	Count	Frequency (%)
58	8	1.1%
53	1	0.1%
50	37	5.0%
49	5	0.7%
48	6	0.8%
47	24	3.2%
46	2	0.3%
43	24	3.2%
41	34	4.6%
40	58	7.8%

Work load Average/day
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	38
Distinct (%)	5.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	271.4902351

Minimum	205.917
Maximum	378.884
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	205.917
5-th percentile	222.196
Q1	244.387
median	264.249
Q3	294.217
95-th percentile	343.253
Maximum	378.884
Range	172.967
Interquartile range (IQR)	49.83

Descriptive statistics

Standard deviation	39.05811619
Coefficient of variation (CV)	0.1438656391
Kurtosis	0.6181879633
Mean	271.4902351
Median Absolute Deviation (MAD)	20.604
Skewness	0.9614566084
Sum	200902.774
Variance	1525.53644
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
222.196	36	4.9%
264.249	33	4.5%
237.656	32	4.3%
343.253	29	3.9%
265.017	28	3.8%
284.853	25	3.4%
308.593	24	3.2%
268.519	23	3.1%
284.031	22	3.0%
244.387	22	3.0%
Other values (28)	466	63.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
205.917	21	2.8%
222.196	36	4.9%
230.29	20	2.7%
236.629	19	2.6%
237.656	32	4.3%
239.409	13	1.8%
239.554	19	2.6%
241.476	22	3.0%
244.387	22	3.0%
246.074	16	2.2%

Value	Count	Frequency (%)
378.884	16	2.2%
377.55	16	2.2%
343.253	29	3.9%
330.061	11	1.5%
326.452	20	2.7%
313.532	15	2.0%
308.593	24	3.2%
306.345	18	2.4%
302.585	18	2.4%
294.217	19	2.6%

Hit target
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	13
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	94.58783784

Minimum	81
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	81
5-th percentile	88
Q1	93
median	95
Q3	97
95-th percentile	99
Maximum	100
Range	19
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	3.779313134
Coefficient of variation (CV)	0.03995559282
Kurtosis	2.419042289
Mean	94.58783784
Median Absolute Deviation (MAD)	2
Skewness	-1.261708179
Sum	69995
Variance	14.28320777
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
93	105	14.2%
99	102	13.8%
97	89	12.0%
92	79	10.7%
96	75	10.1%
95	75	10.1%
98	66	8.9%
91	45	6.1%
94	34	4.6%
88	28	3.8%
Other values (3)	42	5.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
81	19	2.6%
87	12	1.6%
88	28	3.8%
91	45	6.1%
92	79	10.7%
93	105	14.2%
94	34	4.6%
95	75	10.1%
96	75	10.1%
97	89	12.0%

Value	Count	Frequency (%)
100	11	1.5%
99	102	13.8%
98	66	8.9%
97	89	12.0%
96	75	10.1%
95	75	10.1%
94	34	4.6%
93	105	14.2%
92	79	10.7%
91	45	6.1%

Disciplinary failure
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	700
1	40

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Most occurring characters

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	700	94.6%
1	40	5.4%

Education
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1	611
3	79
2	46
4	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Most occurring characters

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	611	82.6%
3	79	10.7%
2	46	6.2%
4	4	0.5%

Son
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	298
1	229
2	156
4	42
3	15

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	1
3rd row	0
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Most occurring characters

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	298	40.3%
1	229	30.9%
2	156	21.1%
4	42	5.7%
3	15	2.0%

Social drinker
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

1	420
0	320

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Most occurring characters

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	420	56.8%
0	320	43.2%

Social smoker
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.9 KiB

0	686
1	54

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	740
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Most occurring characters

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	740	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	740	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	740	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	686	92.7%
1	54	7.3%

Pet
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7459459459

Minimum	0
Maximum	8
Zeros	460
Zeros (%)	62.2%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	4
Maximum	8
Range	8
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.318258291
Coefficient of variation (CV)	1.767230318
Kurtosis	9.67482687
Mean	0.7459459459
Median Absolute Deviation (MAD)	0
Skewness	2.735715439
Sum	552
Variance	1.737804923
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	460	62.2%
1	138	18.6%
2	96	13.0%
4	32	4.3%
8	8	1.1%
5	6	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	460	62.2%
1	138	18.6%
2	96	13.0%
4	32	4.3%
5	6	0.8%
8	8	1.1%

Value	Count	Frequency (%)
8	8	1.1%
5	6	0.8%
4	32	4.3%
2	96	13.0%
1	138	18.6%
0	460	62.2%

Weight
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	26
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	79.03513514

Minimum	56
Maximum	108
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	56
5-th percentile	56
Q1	69
median	83
Q3	89
95-th percentile	98
Maximum	108
Range	52
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	12.88321051
Coefficient of variation (CV)	0.1630061173
Kurtosis	-0.9139276214
Mean	79.03513514
Median Absolute Deviation (MAD)	11
Skewness	0.01700137215
Sum	58486
Variance	165.977113
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
89	113	15.3%
69	85	11.5%
65	61	8.2%
83	55	7.4%
56	46	6.2%
90	40	5.4%
73	37	5.0%
98	35	4.7%
67	30	4.1%
95	29	3.9%
Other values (16)	209	28.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
56	46	6.2%
58	7	0.9%
63	20	2.7%
65	61	8.2%
67	30	4.1%
68	13	1.8%
69	85	11.5%
70	15	2.0%
73	37	5.0%
75	19	2.6%

Value	Count	Frequency (%)
108	5	0.7%
106	19	2.6%
100	2	0.3%
98	35	4.7%
95	29	3.9%
94	4	0.5%
90	40	5.4%
89	113	15.3%
88	29	3.9%
86	24	3.2%

Height
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	14
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	172.1148649

Minimum	163
Maximum	196
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	163
5-th percentile	167
Q1	169
median	170
Q3	172
95-th percentile	182
Maximum	196
Range	33
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	6.03499453
Coefficient of variation (CV)	0.03506376126
Kurtosis	7.317235494
Mean	172.1148649
Median Absolute Deviation (MAD)	2
Skewness	2.566059693
Sum	127365
Variance	36.42115898
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
170	166	22.4%
172	155	20.9%
169	95	12.8%
171	83	11.2%
178	57	7.7%
168	48	6.5%
167	34	4.6%
196	29	3.9%
165	24	3.2%
182	20	2.7%
Other values (4)	29	3.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
163	6	0.8%
165	24	3.2%
167	34	4.6%
168	48	6.5%
169	95	12.8%
170	166	22.4%
171	83	11.2%
172	155	20.9%
174	8	1.1%
175	8	1.1%

Value	Count	Frequency (%)
196	29	3.9%
185	7	0.9%
182	20	2.7%
178	57	7.7%
175	8	1.1%
174	8	1.1%
172	155	20.9%
171	83	11.2%
170	166	22.4%
169	95	12.8%

Body mass index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.67702703

Minimum	19
Maximum	38
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	19
5-th percentile	19
Q1	24
median	25
Q3	31
95-th percentile	32
Maximum	38
Range	19
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	4.285452223
Coefficient of variation (CV)	0.1606420468
Kurtosis	-0.3143750012
Mean	26.67702703
Median Absolute Deviation (MAD)	3
Skewness	0.3050456554
Sum	19741
Variance	18.36510076
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
31	147	19.9%
25	126	17.0%
24	86	11.6%
23	75	10.1%
28	59	8.0%
19	46	6.2%
30	40	5.4%
22	35	4.7%
27	24	3.2%
32	24	3.2%
Other values (7)	78	10.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
19	46	6.2%
21	22	3.0%
22	35	4.7%
23	75	10.1%
24	86	11.6%
25	126	17.0%
27	24	3.2%
28	59	8.0%
29	23	3.1%
30	40	5.4%

Value	Count	Frequency (%)
38	19	2.6%
36	5	0.7%
35	2	0.3%
34	1	0.1%
33	6	0.8%
32	24	3.2%
31	147	19.9%
30	40	5.4%
29	23	3.1%
28	59	8.0%

Absenteeism time in hours
Real number (ℝ_≥0)

ZEROS

Distinct	19
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.924324324

Minimum	0
Maximum	120
Zeros	44
Zeros (%)	5.9%
Negative	0
Negative (%)	0.0%
Memory size	5.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	2
median	3
Q3	8
95-th percentile	24
Maximum	120
Range	120
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	13.3309981
Coefficient of variation (CV)	1.925241724
Kurtosis	38.77730708
Mean	6.924324324
Median Absolute Deviation (MAD)	2
Skewness	5.720727863
Sum	5124
Variance	177.7155104
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
8	208	28.1%
2	157	21.2%
3	112	15.1%
1	88	11.9%
4	60	8.1%
0	44	5.9%
16	19	2.6%
24	16	2.2%
40	7	0.9%
5	7	0.9%
Other values (9)	22	3.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	44	5.9%
1	88	11.9%
2	157	21.2%
3	112	15.1%
4	60	8.1%
5	7	0.9%
7	1	0.1%
8	208	28.1%
16	19	2.6%
24	16	2.2%

Value	Count	Frequency (%)
120	3	0.4%
112	2	0.3%
104	1	0.1%
80	3	0.4%
64	3	0.4%
56	2	0.3%
48	1	0.1%
40	7	0.9%
32	6	0.8%
24	16	2.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	ID	Reason for absence	Month of absence	Day of the week	Seasons	Transportation expense	Distance from Residence to Work	Service time	Age	Work load Average/day	Hit target	Disciplinary failure	Education	Son	Social drinker	Social smoker	Pet	Weight	Height	Body mass index	Absenteeism time in hours
0	11	26	7	3	1	289	36	13	33	239.554	97	0	1	2	1	0	1	90	172	30	4
1	36	0	7	3	1	118	13	18	50	239.554	97	1	1	1	1	0	0	98	178	31	0
2	3	23	7	4	1	179	51	18	38	239.554	97	0	1	0	1	0	0	89	170	31	2
3	7	7	7	5	1	279	5	14	39	239.554	97	0	1	2	1	1	0	68	168	24	4
4	11	23	7	5	1	289	36	13	33	239.554	97	0	1	2	1	0	1	90	172	30	2
5	3	23	7	6	1	179	51	18	38	239.554	97	0	1	0	1	0	0	89	170	31	2
6	10	22	7	6	1	361	52	3	28	239.554	97	0	1	1	1	0	4	80	172	27	8
7	20	23	7	6	1	260	50	11	36	239.554	97	0	1	4	1	0	0	65	168	23	4
8	14	19	7	2	1	155	12	14	34	239.554	97	0	1	2	1	0	0	95	196	25	40
9	1	22	7	2	1	235	11	14	37	239.554	97	0	3	1	0	0	1	88	172	29	8

Last rows

	ID	Reason for absence	Month of absence	Day of the week	Seasons	Transportation expense	Distance from Residence to Work	Service time	Age	Work load Average/day	Hit target	Education	Son	Social drinker	Pet	Weight	Height	Body mass index	Absenteeism time in hours
730	6	22	7	3	1	189	29	13	33	264.604	93	1	2	0	2	69	167	25	16
731	34	23	7	4	1	118	10	10	37	264.604	93	1	0	0	0	83	172	28	2
732	10	22	7	4	1	361	52	3	28	264.604	93	1	1	1	4	80	172	27	8
733	28	22	7	4	1	225	26	9	28	264.604	93	1	1	0	2	69	169	24	8
734	13	13	7	2	1	369	17	12	31	264.604	93	1	3	1	0	70	169	25	80
735	11	14	7	3	1	289	36	13	33	264.604	93	1	2	1	1	90	172	30	8
736	1	11	7	3	1	235	11	14	37	264.604	93	3	1	0	1	88	172	29	4
737	4	0	0	3	1	118	14	13	40	271.219	95	1	1	1	8	98	170	34	0
738	8	0	0	4	2	231	35	14	39	271.219	95	1	2	1	2	100	170	35	0
739	35	0	0	6	3	179	45	14	53	271.219	95	1	1	0	1	77	175	25	0

Most frequently occurring

	ID	Reason for absence	Month of absence	Day of the week	Seasons	Transportation expense	Distance from Residence to Work	Service time	Age	Work load Average/day	Hit target	Education	Social drinker	Weight	Height	Body mass index	Absenteeism time in hours	# duplicates
2	3	27	2	4	2	179	51	18	38	251.818	96	1	1	89	170	31	3	4
14	22	27	4	6	3	179	26	9	30	246.288	91	3	0	56	171	19	2	4
3	3	27	2	4	2	179	51	18	38	264.249	97	1	1	89	170	31	2	3
5	3	27	2	6	2	179	51	18	38	251.818	96	1	1	89	170	31	3	3
7	3	27	3	4	2	179	51	18	38	222.196	99	1	1	89	170	31	2	3
8	3	27	3	5	2	179	51	18	38	222.196	99	1	1	89	170	31	3	3
0	3	23	7	6	1	179	51	18	38	239.554	97	1	1	89	170	31	2	2
1	3	27	2	2	2	179	51	18	38	264.249	97	1	1	89	170	31	2	2
4	3	27	2	5	2	179	51	18	38	264.249	97	1	1	89	170	31	2	2
6	3	27	2	6	2	179	51	18	38	264.249	97	1	1	89	170	31	2	2

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII